Machine Learning Takes a Leading Role in Pay-Per-Click

Machine Learning Takes a Leading Role in Pay-Per-Click

While the ‘art’ of digital advertising will never lose the human element, marketers’ workloads are rapidly shifting as automation and machine learning take a leading role. 

With such fierce competition in the Pay-per-click (PPC) marketplace, it’s no wonder that marketers are turning to machine learning for a competitive edge. For those not familiar with the technology, machine learning refers to a system that uses automation to analyze a wide range of data and near-instantly builds insights based on patterns in the data. 

Over three quarters of enterprises are currently using artificial intelligence and machine learning to enhance customer satisfaction. In particular, these organizations note increases in sales of new products and services by more than 10%. Companies are turning to machine learning in part due to rising market expectations—8 out of 10 frequent shoppers say they will only buy from companies that personalize their shopping experience.

For example, when you log into your Instacart account, you may notice recommended items based on your past purchasing history. The more you purchase, the more relevant the recommendations become. This is machine learning at work.

The rise of the machines

For PPC advertising, we see enormous potential for machine learning. We’ve worked with companies that report, among other results:

  • Reduced bounce rates for paid media campaigns 
  • Increased conversion rates 
  • Reduced cost per acquisition

Here’s how machine learning achieves these results.

  1. Better customer experiences. People are bombarded with ads, and most of them are pretty good. So how can a brand differentiate itself? It can provide higher-than-expected customer experiences, from the ad to the post-click experience and through the conversion process. Machine learning can help inform this process and strategy by better understanding the customer (and even predicting what type of experience they prefer). This allows marketers to  create instant variations of page layouts and designs, enabling personalized narratives for every customer.
  2. Higher ad relevance. Higher ad relevance positions a brand to succeed with the customer and the advertising platform. Platforms like Google and Facebook reward relevant ad messaging with higher placement and lower costs In other words, higher relevance helps to reduce cost-per-acquisition while boosting conversion rates.
  3. Stronger testing. Part of machine learning’s advantage is that it can give automated systems the insights they need to perform multiple actions simultaneously. For example, instead of A/B testing, machine learning can simultaneously learn from ad traffic across multiple variations of a landing page. This allows for faster insight into several strategies, helping advertisers double down on the best-performing pages faster.

The role of the marketer

Machine learning cannot operate successfully without direction and strategy, and that is where the marketer enters. Marketers who understand how to apply machine learning achieve the most significant results. In addition, marketers are required to  synthesize information and insights gathered from various machine learning activities. Thanks to machine learning, marketers can put together insights into customer behavior, UX design preferences, and ongoing trends to select the best course of action. To learn more about how machine learning—and the marketers who love it—will prosper in 2022, check out our ebook, Machine + Marketer = Conversion Advertising in 2022.

Hunter Sunrise
by Hunter Sunrise

As Vice President of Marketing, Hunter’s day-to-day mission is to uncover opportunities for authentic connections and experiences. Using this lens, he has driven success across brand, content, omnichannel, GTM, and growth marketing initiatives. Outside of work, you can find Hunter analyzing the complexity of a sip of wine (he is a Master Sommelier).

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